Global: algorithm: CRNN use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 save_model_dir: output save_epoch_step: 3 eval_batch_step: 2000 train_batch_size_per_card: 256 test_batch_size_per_card: 256 image_shape: [3, 32, 100] max_text_length: 25 character_type: en loss_type: ctc reader_yml: ./configs/rec/rec_benchmark_reader.yml pretrain_weights: Architecture: function: ppocr.modeling.architectures.rec_model,RecModel Backbone: function: ppocr.modeling.backbones.rec_resnet_vd,ResNet layers: 34 Head: function: ppocr.modeling.heads.rec_ctc_head,CTCPredict encoder_type: rnn SeqRNN: hidden_size: 256 Loss: function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss Optimizer: function: ppocr.optimizer,AdamDecay base_lr: 0.001 beta1: 0.9 beta2: 0.999
